张家川高血压月发病率的组合预测模型

The combination forecasting model of monthly hypertensive incidence in Zhangjiachuan

在医学卫生领域,疾病受到许多因素的影响,很难用结构式的因果模型加以解释。根据其自身变动规律建立时间序列的动态模型是一种行之有效的方法,神经网络也可发挥其独特的预测功能,但是每种单一的预测方法都有一定的局限性,故本文研究了季节性ARIMA模型、神经网络模型以及两者的组合预测模型在张家川地区高血压月发病率中的应用,得出组合预测模型可以得到更好的效果。

In the medical field of health,Disease is affected by many factors. It is difficult to use structure to explain the causal model. The time series dynamic modle and neural network would be effective according to its law.However,Every single model has its limitations.So this paper studied the combination of the two forecasting model to forcast the monthly hypertensive incidence in Zhangjiachuan region